Three Secrets of Creating an Insights-to-Actions Organization
Today, companies are in an “arms race” to create a differentiated analytical capability. Some invest because they want to boost ability to serve customers and enhance profits. Others invest because they perceive “everyone else is doing it” and they have to keep up competitively.
However, “data without action is just trivia,” to quote Steve Schnur of MGM Resorts. The value derived from data is not in the information, but the resulting action. Credit card companies have become quite adept at this; for instance, running real-time data scans and analysis of spending activities to detect fraud and freezing cards to protect their business, cardholders and retailers.
The simple truth is there are only so many levers to pull from data insights to grow a business. Don’t get lost in the choices. The power of analytics is realized when actions from information distilled from data helps to: 1) better identify and meet customer needs, or 2) improve on execution to maximize profit. Ask yourself, “if I knew, what would I do” and then conduct your analysis with the intent of taking action to grow your business and maximize your profit.
Here are three secrets to help business leaders create an insights-to-actions organization:
1. Perfect data is often not a requirement
Your data doesn’t have to be perfect to gain value from it, a concept that data guru James Guszcza has championed in the past. While this is less true for certain applications such as financial reporting for public companies, imperfect data can be frequently used to understand why consumers are behaving the way they are.
For example, CPG companies are using a variety of data sources to become more precise and localized in their understandings of their shopper/consumer segments. To do so, they’ll analyze customer and POS scan data, shopper/loyalty data, panel data, demographic data, economic data and so forth. These datasets are far from perfect and hard to integrate with one another. However, there is still a goldmine of insights waiting to be discovered in this data. For example: How does the Hispanic segment differ from other segments? How does weather impact sales? Why are shoppers switching channels?
2. Delivery makes a big difference
There are many delivery methods to choose from to bring information to light: reports, dashboards, storyboards, visualizations and cockpits to name a few. Edward Tufte, one of the leading researchers on visualization wrote: “Making decisions based on evidence requires the appropriate display of that evidence. Good displays of data help to reveal knowledge relevant to understanding.” He goes on to share his analysis of the tragic Space Shuttle Challenger explosion in 1986. The engineers believed that their data indicated a launch in cold weather could result in catastrophe, but could not create a compelling story to prevent decision makers from launching.
Key considerations to facilitate decisions or actions from information delivery include:
- Audience: Know your audience. If they are not technically savvy, don’t give them multidimensional drill downs and fancy visualization options. You’ll only frustrate them.
- Context: Ensure each fact has context. It’s not enough to share the latest sales number. Are sales going up, or going down? Compared to what? Last year’s sales? This year’s plan?
- Occasion: What decisive event does your information support? What do you want people to do depending on the information they’re getting? What will they do next? If sales are down and the next move would be to consult with the responsible sales executive, do you make this collaboration easy?
- Storytelling: Does your data tell a story, or is it just data? Do you leverage headlines or captions to help your readers? Don’t just provide a bar chart of sales numbers. Sort it. Group it. Highlight the top gainers and decliners (by absolute dollar amount, not by percent of sales)
3. A powerful insights-to-actions framework
Winning with analytics requires more than just advanced technology. It’s still a people game. Some believe that the exponential impact of technology will increasingly reduce the need for people for even higher-end professional jobs like analysis. However, I believe that a person enabled by technology will outperform the technology alone.
Going back to a weather analogy, computer models can predict the conditions for a devastating weather event like a tornado, but trained meteorologist concurrence is required before a warning is issued to the public. This is a step that is essential in maintaining public trust.
To support the important human element of turning data into action as part of smart decision-making, one powerful framework to use is “What, So What, Now What:”'
1) The “what” is the initial data or insight – e.g. sales are flat in this category.
2) The “so what” forces stakeholders to think through the implications of the information. If the comparison period is one month, we might feel differently if sales have been flat for a year. “So what” might lead to an implication such as – if this continues, we may lose advertising or marketing investment dollars, which will further risk sales.
3) “Now what” translates into actions to be taken: What specific steps do we take to reverse the trend and grow sales again?
This is the essential role of the analyst. For too long, technology has kept information inaccessible, and the role of the analyst in the organization has been to be the data jockey chasing numbers on behalf of executives and decision makers. As the technology continues to improve exponentially and data becomes more democratized, the analyst role in the organization must change from an “infomediary” to one who facilitates decision and action.
Get started
Lastly, the advancement of technologies, especially in the cloud, are making solutions to complex data problems more and more accessible. You don’t have to have a perfect understanding of the problem to get started. Many vendors offer trials and limited proofs of concept that allow you to test and learn before you fully commit. Don’t study the problem for long. Get started. Your competitors certainly are.
George Spanos is a CPG industry specialist including more than 18 years of experience with The Hershey Company. He currently serves as VP of Strategic Solutions at ClearStory Data.